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Record W1974999592 · doi:10.1179/016164106x98143

Impact of IVIg on the interaction between activated T cells and microglia

2006· article· en· W1974999592 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeurological Research · 2006
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMicrogliaNeuroscienceImmunologyChemistryPsychologyMedicineInflammation

Abstract

fetched live from OpenAlex

When human microglia are co-cultured with activated human T lymphocytes, several cytokines become up-regulated in significant quantities. This condition can also occur at sites of inflammation in autoimmune inflammatory diseases of the central nervous system (CNS), including multiple sclerosis (MS), where T cells infiltrate the brain tissue and come in proximity to microglia. Therefore, T cell-microglia interaction is a potential avenue of drug therapy to decrease neuroinflammation. An immunomodulator used in autoimmune disorders is intravenous immunoglobulins (IVIg). The mechanisms of IVIg activity in diseases such as MS remain unclear. Here, we report that the application of IVIg to activated T cells leads to their decreased ability to engage microglia. As a result of IVIg treatment of T cells, there were reduced levels of tumor necrosis factor-alpha a and interleukin-10 in T cell-microglia co-culture. Our results add to the understanding of how IVIg may affect inflammation of the CNS.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.171
GPT teacher head0.401
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it